T one individual is fatter than another, and

Transcription

1 Family-line and Socioeconomic Factors in Fatness and Obesity Stanley M. Garn, PhD here are hundreds of explanations for why T one individual is fatter than another, and why some people are truly obese. Explanations range from the sensory (involving differences in taste and olfactory acuity), to neuroendocrine, to metabolic, to the mode and amount of feeding in early infancy, to the composition of the diet. To some, obesity represents an ancient adaptation to cyclical fluctuations in food availability. To others, obesity simply reflects a lack of willpower or the summed results of food availability and decreased opportunities for energy expenditure. There is some evidence to support each of these explanations and dozens of others, including failures in the appetite-regulating mechanisms and individual differences in the deposition patterns of nonpigmented fat. Of all the data amassed on fatness levels and on obesity, as variously defined, two sets of observations command the most attention. The first is that above-average fatness and obesity are concentrated in particular families, ie, that fatness runs along family lines. The child of one obese parent is more likely to be obese,2.increasingly so if both parents are obese,3 even more so if the grandparents are obese as The second observation has to do with socioeconomic status (SES) as measured by income, education, and occupation. Though poorer children of both sexes are leaner than their more affluent peer^,^,^ the Dr Garn is a Fellow, Center for Human Growth and Development; Professor of Nutrition, School of Public Health; and Professor of Anthropology, The University of Michigan, Ann Arbor, MI relationship between socioeconomic status and fatness is inverse among adult women, often dramatically SO.^ At age 50 the impoverished woman averages 8 kg more in weight than the higher-income woman, yet the poorer woman is sh~rter.~,~ The existence of positive parent-child correlations in fatness is unquestionable, given tens of thousands of observations. The magnitudes of the mother-child or father-child correlations approximate 0.25, as might be expected for polygenic inheritance.1 Sibling correlations for measured fatness (subscapular, triceps, iliac, or abdominal) are also positive and somewhat higher than 0.25, as would be expected assuming the genetic hypothesis. O If we make use of parental fatness pairings from lean x lean through obese x obese, and including the intermediate categories (medium x medium, medium x lean, medium x obese), the fatness levels of their children increase in agreeably stepwise fashion, achieving textbook perfection. One might assume that the level of fatness is hereditary and additive, were it not for still other observations. One additional observation is that spouses also resemble each other in fatness levels, which might be due to selective mating, but which could also be due to years of living and eating together. A second observation is that parent-child and sibling correlations in fatness actually increase during the growing years, which could represent timing effects, but might also reflect the cumulative effects of communal living. A third observation is that parent-child fatness correlations decrease after the children become adults and are no longer living with their parents. * A fourth observation is that NUTRITION REVIEWSNOL 44, NO 12/DECEMBER

2 family members still living together show synchronic fatness changes, ie, they go up and down in fatness level together.13 Since mothers and fathers are genetically unrelated individuals and average more than 2 decades older than their children, it is difficult to ascribe synchronic fatness changes to genes held in common. As with decreased fatness correlations when the generations no longer live together, nongenetic and environmental effects must be given serious attention. The alternative model to genetically related individuals living together is either 1) genetically unrelated individuals living together, or 2) genetically related individuals living apart. Spouses are one example of the first alternative model, and there are systematic spousal similarities in fatness. Adopted children compared with adoptive parents also comprise examples of the first alternative model and they too show similarities in fatne~s. ~, ~ This is contrary to genetic expectations, but there are complications introduced by the age at adoption, the duration of adoption, the type of adoption, and even seasonal fluctuations in fatness levels which may inflate apparent fatness similarities. The second alternative model, that of genetically related individuals living apart, is well represented by the data from the Danish Adoption Study, involving older parents and their genetic progeny studied as adults.16 Though the selfreported weight-for-height data do suggest similarities in these long-separated parentchild pairs, there are limitations in weight-forheight or the Body Mass Index (wt/ht2). Weight-for-height is affected by relative leg length (or body proportions) and it measures both the lean body mass and the weight of fat to equal degree. Therefore, the older Danish parents and their long-separated adult children may be similar in fatness, or the weight-forheight data may reflect similarities in body proportions and the size of the lean body mass. Many workers have challenged weight-forheight as a valid measure of adip~sity. ~~ ~ In theory, fatness comparisons of monozygotic and dizygotic twins should do much to resolve the nature-nurture controversy and should provide numeric estimates of the heritability of human fatness, symbolized by H2. In practice, however, such comparisons have been disappointing, for technical (methodological) and other reasons. Since the reliability of fatness measurements is only? 5 percent at best, actual monozygotic twin correlations necessarily fall below the theoretic maximum of 1.OO. Dizygotic twin correlations for fatness should approximate those for singleton siblings but, in practice, are somewhat higherup to 0.50-indicating that environmental factors tend to inflate all twin (and triplet) fatness resemblance^.^^ Moreover, the age effect again comes into play, with monozygotic twins becoming less alike in fatness as they reach adulthood, not infrequently differing by * 1 Z-score (ie, standard deviation unit) or more. The most recent studies and data analyses made in Canada, estimating the genetic and environmental sources of fatness variability, tend to give common genes second place to environment when it comes to fatness, besides indicating the need for very large samples as American twin-registering studies again show that monozygotic twins similarities are less than perfect.21 Possibly, the ultimate editorial comment on fatness determinants comes from Mason s often-cited observation that obese adults and elderly adults in England tend to be owners of obese pets.22 One assumption often made in fatness studies is that higher levels of fatness are more or less constant, meaning that the obese remain obese over prolonged periods of time. This assumption is compromised to some extent by the normal volatility of fatness on the part of the obese, which may be considerable over a 1- year period.23 Some of the obese are gaining in fatness and some are losing fatness at any given time. Yet when it comes to the long-term predictability of fatness, from infancy through to adulthood, nearly all investigators have come to the same conclusions. Obese infants, as variously defined, do tend to remain obese as adolescents or as adults, more often than chance would with risk ratios or relative risks of 1.6 to 1.8. Yet most obese babies and infants do not mature into obese adults. The majority of obese adult males do not remain obese for 2 decades, either, though obesity in young adulthood is still a risk factor for middle-aged obesity in the male.27 The fact 382 NUTR/T/ON REV/EWS/VOL 44, NO 12/DECEMBER 1986

3 that the obese do not necessarily remain obese has been explained by the suggestion that there may be different types of obesity (juvenile-onset, adolescent-onset, and adultonset) with different causes and courses. It becomes important, therefore, to ascertain why some infants start obese and remain obese while most do not, why some obese adult males lose fatness level, and why most obese adult females do not. Maturational Timing and Fatness Given the volatility of fatness, the proportion of the obese who become less than obese and the proportion of lean individuals who later become obese, it is intriguing to find one biological variable that relates to fatness level, lifelong. That variable is menarcheal timing, ie, the age at menarche, which not only predicts fatness in the woman herself, but also predicts fatness in her offspring of both sexes. Early maturing women weigh more and are fatter by the third decade, and increase in weight and fatness thereafter, becoming 4 kg heavier and 30 percent fatter by the fourth Even in the sixth and seventh decades, earlymaturing women are fatter than their late-maturing peers. Studied prospectively, both the sons and the daughters of early-maturing women are fatter in infancy, childhood, adolescence, and into adulthood-through to middle age. Obese boys and girls and men and women tend to be the progeny of early-maturing mothers. Lean boys and girls and men and women tend to be the sons and daughters of late-maturing mothers. Exactly how maternal maturity timing determines or controls fatness level is not clear, but the differences are considerable and they cross generational lines. It may be that maturity timing is one expression of the genetic part of fatness variance, and that it is the early-maturer who starts fat and stays fat, ie, the individual who tracks in relative fatness, lifelong.30 Socioeconomic Aspects of Fatness and Obesity In contrast to the biologic determinants of fatness level and obesity, which reveal level after level of complexity, socioeconomic determinants of fatness level are simpler to de- scribe; they are based on still larger samples, but with surprising outcomes. Least surprising is the fact that impoverished boys and girls and poverty-level men are leaner in most countries and most populations studied. Whether defined by income, occupation, education, or house type, low SES is associated with smaller size and less fat in both boys and girls, compared with their more affluent peers of higher SES. Because food is costly, and because the poor have lower purchasing power arid often larger families, with less access to medical care and less stringent supervision of activity levels, energy intake and energy expenditure together would seem to be an adequate explanation for such worldwide differences in measured fatness and in the risk of being obese. When we turn to adult women, and to girls older than age 15, SES is inversely rather than positively (or directly) related to fatness level. This is uniformly true in the massive data of the Ten-state Nutrition Survey (TSNS), the data of the National Health and Nutrition Examination Surveys (NHANES), and the data of the Tecumseh Community Health Studie~.~,~**~ In all these studies, and in other studies in Western countries, low-income women are heavier, fatter, and more often obese. More affluent women (though taller) are lighter in weight and leaner, often to a considerable degree. A 12-kg (30-lb) difference in weight and a larger difference in fatness is not unusual in comparing poverty-level and above-median income groups of women in the middle years. Indeed, there is a striking inverse relationship between SES and fatness level in women. These data may be restated by saying that poorer, leaner preadolescent girls become poorer, fatter adult women, while richer, fatter girls mature into richer, leaner women. It is difficult to explain this socioeconomic reversal of fatness in the female by invoking the sensory hypothesis, set-point theory, adipocyte size and number, or most genetic or physiologic explanations. Clearly, the richer women respond to the message of leaness carried by the print, picture, and electronic media, but why do the magazines, newspapers, and television messages fail to reach the poorer women? Why does the reversal take place at adolescence, around age 15? Why do more NUTRITION REVIEWSNOL 44, NO 12/DECEMBER

4 affluent women fit the oft-repeated dictum of the late Wallis Warfield Simpson ( No woman can be too rich or too thin ), and why do poor women fail to do so? Why are poor women at much greater risk of obesity despite their lower purchasing power? Why do low SES women fail to become weight watchers? The direction (but not the magnitude) of the socioeconomic difference in fatness is the same for children the world around, whether SES is measured by Warner s ranks, income relative to needs, the Bureau of Census Socioeconomic Index, or house types and holdings. Poorer children from larger families with lower purchasing power, less knowledge of nutrition, and experiencing larger cyclical fluctuations in the food supply, are leaner and have lower lipid levels, serum and urinary vitamins, and serum albumin levels than their more affluent peers. They are also smaller, and mature later. There has been some confusion in summarizing these socioeconomic differences in fatness, in part because the directions are different for children of both sexes and adult women, but not for adult men. If fatness is described as poverty-related, that statement must be explicit as to age and sex. There has also been confusion in generalizing the socioeconomic directions of fatness because American and English socioeconomic rankings are arranged in different orders (the English I corresponding to the American high ), leading to seeming differences in direction. Still further confusion arises from comparing mean or median levels of fatness, or the percent deemed obese or the percent deemed superobese by socioeconomic level. A smaller socioeconomic difference in skinfold thickness may be associated with a seemingly large difference in the incidence of obesity, and a still larger difference in the proportion of individuals deemed superobese. As with the quantification of socioeconomic status, by index numbers or by ranks, the expression of fatness levels and differences can cause confusion even among experienced investigators. Among American adults, the relationship between SES and fatness is curvilinear in both sexes, being lowest below the poverty level, then rising, then falling again. Among men, fatness levels increase through medium in- come levels; then they decrease. Among women, fatness levels peak at poverty level (at which point wives often weigh as much as their husbands); then fatness decreases as income or income relative to needs goes up. For the highest income levels, sparsely represented in national surveys, the level of fatness and the incidence of obesity is low in both sexes; the beautiful people of the society pages are generally lean. How the SES continuum is cut makes considerable difference to the results and to the generalizations that can be made. Socioeconomic Differences and Fatness Norms While socioeconomic differences in the level of fatness and the incidence of obesity, and the socioeconomic reversal of fatness in the female, raise questions of etiology and mechanisms, their existence and magnitude serve as useful warnings in diagnosing obesity and suggesting recommended or ideal levels of fatness. Population data, such as the data from the NHANES, include a mixture of poor and affluent Americans who differ in fatness level. Who provides better reference data for normative use, the poor or the rich? Since insurance data on mortality reflect the experience of a rather select group of insured white individuals, are the weight-for-height values associated with minimum long-term mortality applicable to other population segments? Since the percentiles for fatness in the various NHANES cycles include a mixture of leaner smokers and fatter nonsmokers, should we exclude the former in defining obesity? Since the 1959 and 1979 insurance data also comprise a mixture of leaner smokers and fatter nonsmokers, should these data be censored to exclude the smokers with their poorer life expectancy? Questions such as these, and their answers, are of great practical importance in deciding who is too fat and what level of fatness is ideal for fitness or long-term survival. Socioeconomic differences in fatness also bear on sibling similarities in fatness during the growing years, on like-sexed sibling similarities during the adult years, and on similarities between adopted children as well. They bear also on black-white differences in fatness, explaining (in the statistical sense) the greater fatness 384 NUTRITION REVIEWSNOL 44, NO lz/december 1986

5 of black women and the lesser fatness of black children and black males. The greater fatness of American Indian women is also explicable in terms of their lower income levels, and so are the higher birthweights of Cree Indian babies. Most students of fatness and obesity accept the role of both genetic and social factors in determining the fatness level of any individual, refusing to be categorized as strict hereditarians or complete environmentalists just to please the working press. The question to be asked is not which factor is involved in fatness level, but how much of each, under the conditions of a given study. Despite the large fatness differences between poor women and rich women, and fatness differences between Americans and their cousins abroad, there is considerable interpersonal variance that can be genetic in nature. Despite the highest estimates of heritability, in particular studies, there is a considerable fraction of fatness variance attributable to nongenetic factors. But various estimates of the heritability of fatness vary from under 35 percent in one recent study3 to over 80 percent in another recent study;21 and twinstudy estimates were viewed as unrealistic in a third study.20 Therefore, fractionating the genetic and nongenetic components of fatness may still be more statistical than actual, even with environment specifically subtracted from the family-line estimates.32 Skinfolds, weight, and relative weight do yield different estimate~.~~ Indeed, many of the established investigators in the fatness field are known for their contributions in both directions, derived from different study samples and different investigative designs. While there are innumerable suggestions in the published literature as to how the obese and the lean differ from each other-in their frequency of eating, amounts of food consumed, or response to caloric deprivation-these differences may reflect the consequences of being obese and lean, and not their causes. (They may also reflect editorial policies that favor positive findings, but allow the 5-percent level of significance when many different measurements are compared.) Despite the hard-core obese who are alleged to be resistant to all forms of therapy, including surgical intervention, it is encouraging to discover in population contexts that the majority of obese men do not remain obese. It is equally encouraging to learn that only a minority of obese infants mature into obese adults. The dynamics of fatness change, including synchronic fatness change among family members living together, may be more revealing than the statistics of fatness level, especially among obese individuals who are notably fatness-volatile. Obese members of nonobese families may offer better insight into the development of obesity than obese members of obese families with half-a-dozen relatives reinforcing their habits. Spontaneously obese monkeys in primate colonies may help our thinking, as may prisoners restricted to prison food, and more sophisticated experimental designs to separate the effects of living together and genes held in common S Matsuki and R Yoda, Keio J Med20: , SM Garn and DC Clark, fediatrics56: , SM Garn and DC Clark, fediatrics57: , SM Garn, SM Bailey, MA Solomon, and PJ Hopkins, Am JClin Nutr34: , FE Johnston, PVV Hamill, and S Lemeshow, US Dept of Health, Education, and Welfare publication No Government Printing Office, Ten-state Nutrition Survey , US Dept of Health, Education, and Welfare publication No (HSM) Government Printing Office, IJ Rimm and AA Rimm, frev Med3: , PB Goldblatt, ME More, and AJ Stunkard, JAm Med Assoc 192: , SM Garn and AS Ryan, Ecol Food Nutr 10: , SM Garn, SM Bailey, and ITT Higgins in Childhood Prevention of Atherosclerosis and Hypertension. RM Lauer and RB Shekelle, Editors, pp Raven Press, New York, NY, SM Garn, SM Bailey, and PE Cole in Nutrition, Physiology, and Obesity. R Schemmel, Editor, pp CRC Press, Palm Beach, FL, SM Garn, M LaVelle, and JJ Pilkington, Marr Fam Rev 7: 33-47, SM Garn, SM Bailey, and PE Cole, Am J Clin Nutr32: , 1979 NUTRITION REVIEWSNOL 44, NO 12/DECEMBER

Recommended Weight and Body Fat Contents In 1942, Louis Dublin, a statistician at Metropolitan Life Insurance Company, grouped some four million people who were insured with Metropolitan Life into categories

DRIVER SPEED COMPLIANCE WITHIN SCHOOL ZONES AND EFFECTS OF 4 PAINTED SPEED LIMIT ON DRIVER SPEED BEHAVIOURS Tony Radalj Main Roads Western Australia ABSTRACT Two speed surveys were conducted on nineteen

Linking the New York State NYSTP Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. March 2016 Introduction Northwest Evaluation Association

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions October 17, 2006 Simple- and combined-cycle gas turbine power plants fuelled by natural gas are among the bulk power

Autonomous vehicles: potential impacts on travel behaviour and our industry Chris De Gruyter Research Fellow Public Transport Research Group (PTRG) Institute of Transport Studies Department of Civil Engineering

A STUDY ON THE INFLUENCE OF LOCATION AND STORE DESIGN FACTORS WITH REFERENCE TO SELECTED READYMADE GARMENTS SHOP IN TIRUNELVELI K. Pon Abinaya* Dr. Albin D. Robert Lawrence** *II Year MBA student, School

National Household Travel Survey Add-On Use in the Des Moines, Iowa, Metropolitan Area Presentation to the Transportation Research Board s National Household Travel Survey Conference: Data for Understanding

CASE STUDY BUILDING A ROBUST INDUSTRY INDEX BASED ON LONGITUDINAL DATA Hanover built a first of its kind index to diagnose the health, trends, and hidden opportunities for the fastgrowing auto care industry.

Comprehensive Safety Analysis Initiative A R T I C L E S E R I E S BASIC 1: UNSAFE DRIVING Staying on top of safety and compliance under the CSA 2010 initiative will mean getting back to the BASICs. This

Linking the Indiana ISTEP+ Assessments to the NWEA MAP Growth Tests February 2017 Updated November 2017 2017 NWEA. All rights reserved. No part of this document may be modified or further distributed without

RESEARCH BRIEF This Research Brief provides updated statistics on rates of crashes, injuries and death per mile driven in relation to driver age based on the most recent data available, from 2014-2015.

Student-Level Growth Estimates for the SAT Suite of Assessments YoungKoung Kim, Tim Moses and Xiuyuan Zhang November 2017 Disclaimer: This report is a pre-published version. The version that will eventually

Material World How Does the USA Compare? Center for Energy and Environmental Education, University of Northern Iowa WR teacher training 24-25/Website/Lessons/Material World How Does the USA Compare? Written

N F O C F g r o u p Seat Belt Survey Q1. When travelling in a car, do you wear your seat belt all of the time, most of the time, some of the time, or never? The majority of Canadians (85%) wear their seat

DOT HS 89 616 U.S. Department of Transportation National Highway Traffic Safety Administration Traffic Safety Facts 22 A Public Information Fact Sheet on Motor Vehicle and Traffic Safety Published by the

Use the website: http://www.safeprogram.com/videos.php?action=1 if you need to view the videos again or if you were absent. The Power of Your Seatbelt Notice that the driver seems to be very sleepy Consider

U.S. Department of Transportation National Highway Traffic Safety Administration Traffic Safety Facts 1995 exceeding the posted speed limit or driving too fast for conditions is one of the most prevalent

RISK Despite critics claims, SUVs are saving lives. The Truth About Light Trucks The american love affair with the automobile has grown to include the class of vehicles known as light trucks, which includes

US Consumer Battery Sales & Available for Collection 2014 to 2020 May 2016 A report commissioned by Call2Recycle, Inc. Prepared by Kelleher Environmental in association with SAMI Environmental 2016 Call2Recycle,

An Investigation of the Distribution of Driving Speeds Using In-vehicle GPS Data Jianhe Du Lisa Aultman-Hall University of Connecticut Problem Statement Traditional speed collection methods can not record

Klaus Sommer Hanover, December 15, 2011 Content International requirements and expectations for E-Mobility Urbanization What are the challenges of individual mobility for international megacities? What

CSA 2010 What You Need to Know With Comprehensive Safety Analysis 2010 (CSA 2010) the Federal Motor Carrier Safety Administration (FMCSA), together with state partners and industry will work to further

Photo courtesy Toyota Motor Sales USA Inc. According to Toyota, as of March 2013, the company had sold more than 5 million hybrid vehicles worldwide. Two million of these units were sold in the US. What

Used Vehicle Supply: Future Outlook and the Impact on Used Vehicle Prices AT A GLANCE When to expect an increase in used supply Recent trends in new vehicle sales Changes in used supply by vehicle segment

2013 PLS Alumni/ae Survey: Overall Evaluation of the Program Summary In the spring 2013, the Program of Liberal Studies conducted its first comprehensive survey of alumni/ae in several decades. The department

Untitled Document Statistics and Facts About Distracted Driving What does it mean to be a distracted driver? Are you one? Learn more here. What Is Distracted Driving? There are three main types of distraction:

Bellwork In a recent year, 73% of first year college students responding to a national survey identified being very well off financially as an important personal goal. A state university finds that 132

Response to Ministry of Justice Consultation Paper Driving Offences and Penalties Relating to Causing Death or Serious Injury January 2017 Introduction This is RoSPA s response to the Ministry of Justice

Correlation to the Common Core State Standards Go Math! 2011 Grade 3 Common Core is a trademark of the National Governors Association Center for Best Practices and the Council of Chief State School Officers.

Green Line LRT: Beltline Recommendation Frequently Asked Questions June 2017 Quick Facts Administration has evaluated several alignment options that would connect the Green Line in the Beltline to Victoria

RoSPA RESPONSE TO THE DRIVING STANDARDS AGENCY CONSULTATION PAPER DRIVER CERTIFICATE OF PROFESSIONAL COMPETENCE 8 FEBRUARY 2006 DRIVER CERTIFICATE OF PROFESSIONAL COMPETENCE This is the response of the

Quality of Life in Neurological Disorders Scoring Manual Version 2.0 March 2015 Table of Contents Scoring Options... 4 Scoring Service... 4 How to use the HealthMeasures Scoring Service, powered by Assessment

Second European Nutrition Conference, Munich 1976 Nutr. Metab. 21: 251 279(1977) Tables of Recommended Nutrient Intakes in Different European Countries Introduction It was decided by the participants of

Specialty Vehicle Institute of America Special Report Summer 2007 Table of Contents About the Specialty Vehicle Institute of America................. 1 What is an All-Terrain Vehicle?.............................

August 3, 2012 DATA BRIEF: Black Employment and Unemployment in July 2012 The unemployment rate for Blacks was 14.1% last month. This is according to the latest report on the nation s employment situation

BASF European Color Report For Automotive OEM Coatings 2017 Blue and gray shades strengthen their positions on European roads BASF European Color Report For Automotive OEM Coatings 2017 The world of automotive

Why do People Die in Road Crashes? Prepared for: Ministry of Transport April 2016 Page 1 of 24 Transport Engineering Research New Zealand Limited (TERNZ) is a research organisation providing high quality

What Is Analysis? Rebecca Jarvis, Ph.D., and Ginger, Ca.T., Eastern Arizona College My desk at home What s on the table Let s list everything that is on the table: two laptops, one opened and one closed;